Skip to main content

New Drug Approvals 2012 - Pt. X - Avanafil (StendraTM)




ATC code: G04BE (partial)
Wikipedia: Avanafil


On April 27th, the FDA approved Avanafil (tradename: Stendra; Research Code: TA-1790), a phosphodiesterase 5 (PDE5) inhibitor for the treatment of erectile dysfunction (ED). ED is a sexual dysfunction characterized by the inability to produce an erection of the penis. The physiologic mechanism of penile erection involves the release of nitric oxide in the corpus cavernosum during sexual stimulation, which in turn activates the enzyme guanylate cyclase, resulting in increased levels of cyclic guanosine monophosphate (cGMP). cGMP produces relaxation of smooth muscle tissues, which in the corpus cavernosum results in vasodilation and increased blood flow. Avanafil (PubChem: CID9869929, ChemSpider: 8045620) enhances the relaxant effects of cGMP by selectively inhibiting PDE5 (ChEMBL: CHEMBL1827; Uniprot: O76074), an enzyme responsible for the degradation of cGMP.

Other PDE5 inhibitors are already available on the market and these include Sildenafil (approved in 1998; tradename: Viagra, Revatio; ChEMBL: CHEMBL192), Tadalafil (approved in 2003; tradename: Cialis; ChEMBL: CHEMBL779) and Vardenafil (approved in 2003; tradename: Levitra; ChEMBL: CHEMBL1520). These other PDE5 inhibitors are also approved for the treatment of pulmonary arterial hypertension (PAH).

PDE5 is an 875 amino acid-long enzyme (EC=3.1.4.35), belonging to the cyclic nucleotide phosphodiesterase family (PFAM: PF00233).

>PDE5A_HUMAN cGMP-specific 3',5'-cyclic phosphodiesterase
MERAGPSFGQQRQQQQPQQQKQQQRDQDSVEAWLDDHWDFTFSYFVRKATREMVNAWFAE
RVHTIPVCKEGIRGHTESCSCPLQQSPRADNSAPGTPTRKISASEFDRPLRPIVVKDSEG
TVSFLSDSEKKEQMPLTPPRFDHDEGDQCSRLLELVKDISSHLDVTALCHKIFLHIHGLI
SADRYSLFLVCEDSSNDKFLISRLFDVAEGSTLEEVSNNCIRLEWNKGIVGHVAALGEPL
NIKDAYEDPRFNAEVDQITGYKTQSILCMPIKNHREEVVGVAQAINKKSGNGGTFTEKDE
KDFAAYLAFCGIVLHNAQLYETSLLENKRNQVLLDLASLIFEEQQSLEVILKKIAATIIS
FMQVQKCTIFIVDEDCSDSFSSVFHMECEELEKSSDTLTREHDANKINYMYAQYVKNTME
PLNIPDVSKDKRFPWTTENTGNVNQQCIRSLLCTPIKNGKKNKVIGVCQLVNKMEENTGK
VKPFNRNDEQFLEAFVIFCGLGIQNTQMYEAVERAMAKQMVTLEVLSYHASAAEEETREL
QSLAAAVVPSAQTLKITDFSFSDFELSDLETALCTIRMFTDLNLVQNFQMKHEVLCRWIL
SVKKNYRKNVAYHNWRHAFNTAQCMFAALKAGKIQNKLTDLEILALLIAALSHDLDHRGV
NNSYIQRSEHPLAQLYCHSIMEHHHFDQCLMILNSPGNQILSGLSIEEYKTTLKIIKQAI
LATDLALYIKRRGEFFELIRKNQFNLEDPHQKELFLAMLMTACDLSAITKPWPIQQRIAE
LVATEFFDQGDRERKELNIEPTDLMNREKKNKIPSMQVGFIDAICLQLYEALTHVSEDCF
PLLDGCRKNRQKWQALAEQQEKMLINGESGQAKRN

Several crystal structures of PDE5 are now available. The catalytic domain of human PDE5 complexed with sildenafil is shown below (PDBe:1tbf)





Preclinical studies have shown that Avanafil strongly inhibits PDE5 (half maximal inhibitory concentration = 5.2 nM) in a competitive manner and is 100-fold more potent for PDE5 than PDE6, which is found in the retina and is responsible for phototransduction. Also, Avanafil has shown higher selectivity (120-fold) against PDE6 than Sildenafil (16-fold) and Vardenafil (21-fold), and high selectivity (>10 000-fold) against PDE1 compared with Sildenafil (380-fold) and Vardenafil (1000-fold). 

Avanafil has also been reported to be a faster-acting drug than Sildenafil, with an onset of action as little as 15 minutes as opposed to 30 minutes for the other drugs.


Avanafil is a synthetic small molecule, with one chiral center. Avanafil has a molecular weight of 483.95 Da, an ALogP of 2.16, 3 hydrogen bond donors and 9 hydrogen bond acceptors and thus fully rule-of-five compliant. (IUPAC: 4-[(3-chloro-4-methoxyphenyl)methylamino]-2-[(2S)-2-(hydroxymethyl)-pyrrolidin-1-yl]-N-(pyrimidin-2-ylmethyl)pyrimidine-5-carboxamide; Canonical Smiles: COC1=C(C=C(C=C1)CNC2=NC(=NC=C2C(=O)NCC3=NC=CC=N3)N4CCC[C@H]4CO)Cl; InChI: InChI=1S/C23H26ClN7O3/c1-34-19-6-5-15(10-18(19)24)11-27-21-17(22(33)28-
13-20-25-7-3-8-26-20)12-29-23(30-21)31-9-2-4-16(31)14-32/h3,5-8,10,12,
16,32H,2,4,9,11,13-14H2,1H3,(H,28,33)(H,27,29,30)/t16-/m0/s1)

The recommended starting dose of Avanafil is 100 mg and should be taken orally as needed approximately 30 minutes before sexual activity. Depending on individual efficacy and tolerability, the dose can be varied to a maximum dose of 200 mg or decreased to 50 mg. The lowest dose that  provides efficacy should be used. The maximum recommended dosing frequency is once per day.

Avanafil is rapidly absorbed after oral administration, with a median Tmax of 30 to 45 minutes in the fasted state and 1.12 to 1.25 hours when taken with a high fat meal. Avanafil is approximately 99% bound to plasma proteins and has been found to not accumulate in plasma. It is predominantely cleared by hepatic metabolism, mainly by CYP3A4 enzyme and to a minor extent by CYP2c isoform. The plasma concentrations of the major metabolites, M4 and M16, are approximately 23% and 29% of that of the parent compound, respectively. The M4 metabolite accounts for approximately 4% of the pharmacologic activity of Avanafil, with an in vitro inhibitory potency for PDE5 of 18% of that of Avanafil. The M16 metabolite has been found inactive against PDE5. After oral administration, Avanafil is excreted as metabolites mainly in the feces (approximately 62% of administrated dose) and to a lesser extent in the urine (approximately 21% of the administrated dose). Avanafil has a terminal elimination  half-life (t1/2) of approximately 5 hours, which is comparable to that of Sildenafil (3-4h) and Vardenafil (4-5h), but very short relative to the very long half-life of Tadalafil (17.5h).

The full prescribing information of Avanafil can be found here.

The license holder is Vivus, Inc.

Comments

Popular posts from this blog

New SureChEMBL announcement

(Generated with DALL-E 3 ∙ 30 October 2023 at 1:48 pm) We have some very exciting news to report: the new SureChEMBL is now available! Hooray! What is SureChEMBL, you may ask. Good question! In our portfolio of chemical biology services, alongside our established database of bioactivity data for drug-like molecules ChEMBL , our dictionary of annotated small molecule entities ChEBI , and our compound cross-referencing system UniChem , we also deliver a database of annotated patents! Almost 10 years ago , EMBL-EBI acquired the SureChem system of chemically annotated patents and made this freely accessible in the public domain as SureChEMBL. Since then, our team has continued to maintain and deliver SureChEMBL. However, this has become increasingly challenging due to the complexities of the underlying codebase. We were awarded a Wellcome Trust grant in 2021 to completely overhaul SureChEMBL, with a new UI, backend infrastructure, and new f

A python client for accessing ChEMBL web services

Motivation The CheMBL Web Services provide simple reliable programmatic access to the data stored in ChEMBL database. RESTful API approaches are quite easy to master in most languages but still require writing a few lines of code. Additionally, it can be a challenging task to write a nontrivial application using REST without any examples. These factors were the motivation for us to write a small client library for accessing web services from Python. Why Python? We choose this language because Python has become extremely popular (and still growing in use) in scientific applications; there are several Open Source chemical toolkits available in this language, and so the wealth of ChEMBL resources and functionality of those toolkits can be easily combined. Moreover, Python is a very web-friendly language and we wanted to show how easy complex resource acquisition can be expressed in Python. Reinventing the wheel? There are already some libraries providing access to ChEMBL d

LSH-based similarity search in MongoDB is faster than postgres cartridge.

TL;DR: In his excellent blog post , Matt Swain described the implementation of compound similarity searches in MongoDB . Unfortunately, Matt's approach had suboptimal ( polynomial ) time complexity with respect to decreasing similarity thresholds, which renders unsuitable for production environments. In this article, we improve on the method by enhancing it with Locality Sensitive Hashing algorithm, which significantly reduces query time and outperforms RDKit PostgreSQL cartridge . myChEMBL 21 - NoSQL edition    Given that NoSQL technologies applied to computational chemistry and cheminformatics are gaining traction and popularity, we decided to include a taster in future myChEMBL releases. Two especially appealing technologies are Neo4j and MongoDB . The former is a graph database and the latter is a BSON document storage. We would like to provide IPython notebook -based tutorials explaining how to use this software to deal with common cheminformatics p

Multi-task neural network on ChEMBL with PyTorch 1.0 and RDKit

  Update: KNIME protocol with the model available thanks to Greg Landrum. Update: New code to train the model and ONNX exported trained models available in github . The use and application of multi-task neural networks is growing rapidly in cheminformatics and drug discovery. Examples can be found in the following publications: - Deep Learning as an Opportunity in VirtualScreening - Massively Multitask Networks for Drug Discovery - Beyond the hype: deep neural networks outperform established methods using a ChEMBL bioactivity benchmark set But what is a multi-task neural network? In short, it's a kind of neural network architecture that can optimise multiple classification/regression problems at the same time while taking advantage of their shared description. This blogpost gives a great overview of their architecture. All networks in references above implement the hard parameter sharing approach. So, having a set of activities relating targets and molecules we can tra

ChEMBL 26 Released

We are pleased to announce the release of ChEMBL_26 This version of the database, prepared on 10/01/2020 contains: 2,425,876 compound records 1,950,765 compounds (of which 1,940,733 have mol files) 15,996,368 activities 1,221,311 assays 13,377 targets 76,076 documents You can query the ChEMBL 26 data online via the ChEMBL Interface and you can also download the data from the ChEMBL FTP site . Please see ChEMBL_26 release notes for full details of all changes in this release. Changes since the last release: * Deposited Data Sets: CO-ADD antimicrobial screening data: Two new data sets have been included from the Community for Open Access Drug Discovery (CO-ADD). These data sets are screening of the NIH NCI Natural Product Set III in the CO-ADD assays (src_id = 40, Document ChEMBL_ID = CHEMBL4296183, DOI = 10.6019/CHEMBL4296183) and screening of the NIH NCI Diversity Set V in the CO-ADD assays (src_id = 40, Document ChEMBL_ID = CHEMBL4296182, DOI = 10.601